The Effect of High Ambient Temperature on the Elderly Population in Three Regions of Sweden

The short-term effects of high temperatures are a serious concern in the context of climate change. In areas that today have mild climates the research activity has been rather limited, despite the fact that differences in temperature susceptibility will play a fundamental role in understanding the exposure, acclimatization, adaptation and health risks of a changing climate. In addition, many studies employ biometeorological indexes without careful investigation of the regional heterogeneity in the impact of relative humidity. We aimed to investigate the effects of summer temperature and relative humidity and regional differences in three regions of Sweden allowing for heterogeneity of the effect over the scale of summer temperature. To do so, we collected mortality data for ages 65+ from Stockholm, Göteborg and Skåne from the Swedish National Board of Health and Welfare and the Swedish Meteorological and Hydrological Institute for the years 1998 through 2005. In Stockholm and Skåne on average 22 deaths per day occurred, while in Göteborg the mean frequency of daily deaths was 10. We fitted time-series regression models to estimate relative risks of high ambient temperatures on daily mortality using smooth functions to control for confounders, and estimated non-linear effects of exposure while allowing for auto-regressive correlation of observations within summers. The effect of temperature on mortality was found distributed over the same or following day, with statistically significant cumulative combined relative risk of about 5.1% (CI = 0.3, 10.1) per °C above the 90th percentile of summer temperature. The effect of high relative humidity was statistically significant in only one of the regions, as was the effect of relative humidity (above 80th percentile) and temperature (above 90th percentile). In the southernmost region studied there appeared to be a significant increase in mortality with decreasing low summer temperatures that was not apparent in the two more northerly situated regions. The effects of warm temperatures on the elderly population in Sweden are rather strong and consistent across different regions after adjustment for mortality displacement. The impact of relative humidity appears to be different in regions, and may be a more important predictor of mortality in some areas

A Spatio-Temporal Analysis of Dengue Fever Transmission in Yogyakarta City, Indonesia

BACKGROUND: Dengue fever remains a major health problem in tropical countries. Some measures had been implemented by the government to control this disease. Apparently, however, these measures were not effective. Therefore, there is a need for a study that provides information to aid the control program. This study aimed at investigating the space-time clustering of dengue fever transmission in Yogyakarta. SUBJECT AND METHODS: This was a retrospective cohort study using surveillance data on dengue fever cases in all subdistricts, Yogyakarta, Indonesia, from January to July 2014. This secondary data was obtained from the Municipality Health Office, Yogyakarta City. The space-time clustering of dengue fever case transmission was analyzed using SaTScan permutation model. RESULT: Dengue fever case transmission was clustered temporarily in several spots during the study period. The clustering of dengue fever transmission differed significantly among sub-districts with Mergangsan sub-district showing the highest cluster (p=0.005). CONCLUSION: There is a significant difference in dengue fever transmission clustering among sub-districts in Yogyakarta City with the highest cluster occurring in Mergangsan sub-district. This finding can be used to guide future study into intervention priority of dengue fever control in Yogyakarta City. Keywords: dengue fever, cluster, space-time analysis, urban, SaTSca

Projecting the risk of mosquito-borne diseases in a warmer and more populated world: a multi-model, multi-scenario intercomparison modelling study

Background: Mosquito-borne diseases are expanding their range, and re-emerging in areas where they had subsided for decades. The extent to which climate change influences the transmission suitability and population at risk of mosquito-borne diseases across different altitudes and population densities has not been investigated. The aim of this study was to quantify the extent to which climate change will influence the length of the transmission season and estimate the population at risk of mosquito-borne diseases in the future, given different population densities across an altitudinal gradient. Methods: Using a multi-model multi-scenario framework, we estimated changes in the length of the transmission season and global population at risk of malaria and dengue for different altitudes and population densities for the period 1951-99. We generated projections from six mosquito-borne disease models, driven by four global circulation models, using four representative concentration pathways, and three shared socioeconomic pathways. Findings: We show that malaria suitability will increase by 1·6 additional months (mean 0·5, SE 0·03) in tropical highlands in the African region, the Eastern Mediterranean region, and the region of the Americas. Dengue suitability will increase in lowlands in the Western Pacific region and the Eastern Mediterranean region by 4·0 additional months (mean 1·7, SE 0·2). Increases in the climatic suitability of both diseases will be greater in rural areas than in urban areas. The epidemic belt for both diseases will expand towards temperate areas. The population at risk of both diseases might increase by up to 4·7 additional billion people by 2070 relative to 1970-99, particularly in lowlands and urban areas. Interpretation: Rising global mean temperature will increase the climatic suitability of both diseases particularly in already endemic areas. The predicted expansion towards higher altitudes and temperate regions suggests that outbreaks can occur in areas where people might be immunologically naive and public health systems unprepared. The population at risk of malaria and dengue will be higher in densely populated urban areas in the WHO African region, South-East Asia region, and the region of the Americas, although we did not account for urban-heat island effects, which can further alter the risk of disease transmission

Validating Search Protocols for Mining of Health and Disease Events on Twitter

BACKGROUND: Twitter is a free social networking and micro-blogging service that enables its users to read and share information with user and media communities in messages no longer than 140-character. In the year of 2016, there were more than 24 million Indonesian twitter users sharing news, events, as well as personal feelings and experiences on Twitter. This study seeks to validate a search protocol of health related terms using real-time Twitter data which can later be used to understand if, and how, twitter can reveal information on the current health situation in Indonesia. In this validation study of mining protocols, we: 1) extracted geo-located conversations related to health and disease postings on Twitter using a set of pre-defined keywords, 2) assessed the prevalence, frequency and timing of such content in these conversations, and 3) validated how this search protocol was able to detect relevant disease tweets. SUBJECT AND METHODS: Groups of words and phrases relevant to disease symptoms and health outcomes were used in a protocol developed in the Indonesian language in order to extract relevant content from geo-tagged Twitter feeds. A supervised learning algorithm using Classification and Regression Tree´s (CART) was used to validate search protocols of disease and health hits comparing to those identified by a team of human experts. The experts categorized tweets as positive or negative in respect to health events. The model fit was evaluated based on prediction perfor-mance. RESULTS: 390 tweets from historical Twitter feeds and 1,145,649 tweets from Twitter stream feeds during the period July 26th to August 1st, 2016. Only twitter hits with health related keywords in the Indonesian language were obtained. The accuracy of predictions of mined hits versus expert validated hits using the CART algorithm showed good validity with AUC beyond 0.8. CONCLUSION: Monitoring of public sentiment on Twitter, combined with contextual knowledge about the disease, can detect health and disease tweets and potentially be used as a valuable real-time proxy for health events over space and time. Keywords: social networking, disease detection, disease early warning, digital epidemiology, big data analysi

Climate Services For Infectious Disease Control: A Nexus Between Public Health Preparedness And Sustainable Development, Lessons Learned From Long-Term Multi-Site Time-Series Analysis Of Dengue Fever In Vietnam

BACKGROUND: Climate services provide valuable information for making actionable, data-driven decisions to protect public health in a myriad of manners. There is mounting global evidence of the looming threat climate change poses to human health, including the variability and intensity of infectious disease outbreaks in Vietnam and other low-resource and developing areas. In light of the Sustainable Development Goals, this study aimed to examine the utility of spatial and time-series analysis, to inform public health preparedness strategies for sustainable urban development, in terms of dengue epidemiology, surveillance, control, and early warnings. SUBJECTS AND METHODS: Nearly 40 years of spatial and temporal (times-series) dataset of meteorological records, including rainfall, temperature, and humidity (among others) which can be predictors of dengue were assembled for all provinces of Vietnam. This dataset was associated with case data reported to General Department of Preventive Medicine, Ministry of Health of Vietnam, during the same period. Time series of climate and disease variables were analyzed for trend and changing pattern over time. The time-series statistical analysis method sought to identify spatial (when possible) and temporal trend, seasonality, cyclical pattern of disease, and to discover anomalous outbreak events, which departed from expected epidemiological pattern, and corresponding meteorological phenomena, such as El Nino Southern Oscillation (ENSO). RESULTS: Analysis yielded largely converged findings with other locations in South East Asia for larger outbreak years and events such as ENSO. Seasonality, trend, and cycle in many provinces were persistent throughout the dataset, indicating strong potential for climate services to be used in dengue early warnings. CONCLUSION: Public health practitioners, having adequate tools for dengue control available, must plan and budget vector control and patient treatment efforts well in advance of large scale dengue epidemics to curb such events with overall morbidity and mortality. Urban and sustainable development in Vietnam might benefit from evidence linking climate change and ill-health events spatially and temporally in future planning. Long term analysis of dengue case data and meteorological records, provided a cases study evidence for emerging opportunities that on how refined climate services, could contribute to protection of public health. Keywords: dengue, Vietnam, climate change, time-series analysis, climate servic

Mortality risk attributable to high and low ambient temperature: a multicountry observational study

Background: Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. Methods: We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature-mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2・5th and 97・5th temperature percentiles. Findings: We analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7・71% (95% empirical CI 7・43-7・91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3・37% (3・06 to 3・63) in Thailand to 11・00% (9・29 to 12・47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80-90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7・29%, 7・02-7・49) than by heat (0・42%, 0・39-0・44). Extreme cold and hot temperatures were responsible for 0・86% (0・84-0・87) of total mortality. Interpretation: Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. Funding: UK Medical Research Council

Mortality burden of diurnal temperature range and its temporal changes: A multi-country study.

Although diurnal temperature range (DTR) is a key index of climate change, few studies have reported the health burden of DTR and its temporal changes at a multi-country scale. Therefore, we assessed the attributable risk fraction of DTR on mortality and its temporal variations in a multi-country data set. We collected time-series data covering mortality and weather variables from 308 cities in 10 countries from 1972 to 2013. The temporal change in DTR-related mortality was estimated for each city with a time-varying distributed lag model. Estimates for each city were pooled using a multivariate meta-analysis. The results showed that the attributable fraction of total mortality to DTR was 2.5% (95% eCI: 2.3-2.7%) over the entire study period. In all countries, the attributable fraction increased from 2.4% (2.1-2.7%) to 2.7% (2.4-2.9%) between the first and last study years. This study found that DTR has significantly contributed to mortality in all the countries studied, and this attributable fraction has significantly increased over time in the USA, the UK, Spain, and South Korea. Therefore, because the health burden of DTR is not likely to reduce in the near future, countermeasures are needed to alleviate its impact on human health

Cold and heat waves in the United States

Extreme cold and heat waves, characterised by a number of cold or hot days in succession, place a strain on people’s cardiovascular and respiratory systems. The increase in deaths due to these waves may be greater than that predicted by extreme temperatures alone. We examined cold and heat waves in 99 US cities for 14 years (1987–2000) and investigated how the risk of death depended on the temperature threshold used to define a wave, and a wave’s timing, duration and intensity. We defined cold and heat waves using temperatures above and below cold and heat thresholds for two or more days. We tried five cold thresholds using the first to fifth percentiles of temperature, and five heat thresholds using the ninety-fifth to ninety-ninth percentiles. The extra wave effects were estimated using a two-stage model to ensure that their effects were estimated after removing the general effects of temperature. The increases in deaths associated with cold waves were generally small and not statistically significant, and there was even evidence of a decreased risk during the coldest waves. Heat waves generally increased the risk of death, particularly for the hottest heat threshold. Cold waves of a colder intensity or longer duration were not more dangerous. Cold waves earlier in the cool season were more dangerous, as were heat waves earlier in the warm season. In general there was no increased risk of death during cold waves above the known increased risk associated with cold temperatures. Cold or heat waves earlier in the cool or warm season may be more dangerous because of a build up in the susceptible pool or a lack of preparedness for cold or hot temperatures

Achieving a 25% reduction in premature non-communicable disease mortality : the Swedish population as a cohort study

Background: The 2012 World Health Assembly set a target for Member States to reduce premature non-communicable disease (NCD) mortality by 25% over the period 2010 to 2025. This reflected concerns about increasing NCD mortality burdens among productive adults globally. This article first considers whether the WHO target of a 25% reduction in the unconditional probability of dying between ages of 30 and 70 from NCDs (cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases) has already taken place in Sweden during an equivalent 15-year period. Secondly, it assesses which population sub-groups have been more or less successful in contributing to overall changes in premature NCD mortality in Sweden. Methods: A retrospective dynamic cohort database was constructed from Swedish population registers in the Linnaeus database, covering the entire population in the age range 30 to 69 years for the period 1991 to 2006, which was used directly to measure reductions in premature NCD mortality using a life table method as specified by the WHO. Multivariate Poisson regression models were used to assess the contributions of individual background factors to decreases in premature NCD mortality. Results: A total of 292,320 deaths occurred in the 30 to 69 year age group during the period 1991 to 2006, against 70,768,848 person-years registered. The crude all-cause mortality rate declined from 5.03 to 3.72 per 1,000 person-years, a 26% reduction. Within this, the unconditional probability of dying between the ages of 30 and 70 from NCD causes as defined by the WHO fell by 30.0%. Age was consistently the strongest determinant of NCD mortality. Background determinants of NCD mortality changed significantly over the four time periods 1991-1994, 1995-1998, 1999-2002, and 2003-2006. Conclusions: Sweden, now at a late stage of epidemiological transition, has already exceeded the 25% premature NCD mortality reduction target during an earlier 15-year period. This should be encouraging news for countries currently implementing premature NCD mortality reduction programmes. Our findings suggest, however, that it may be difficult for Sweden and other late-transition countries to reach the current 25 x 25 target, particularly where substantial premature mortality reductions have already been achieved

Achieving a 25% reduction in premature non-communicable disease mortality : the Swedish population as a cohort study

Background: The 2012 World Health Assembly set a target for Member States to reduce premature non-communicable disease (NCD) mortality by 25% over the period 2010 to 2025. This reflected concerns about increasing NCD mortality burdens among productive adults globally. This article first considers whether the WHO target of a 25% reduction in the unconditional probability of dying between ages of 30 and 70 from NCDs (cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases) has already taken place in Sweden during an equivalent 15-year period. Secondly, it assesses which population sub-groups have been more or less successful in contributing to overall changes in premature NCD mortality in Sweden. Methods: A retrospective dynamic cohort database was constructed from Swedish population registers in the Linnaeus database, covering the entire population in the age range 30 to 69 years for the period 1991 to 2006, which was used directly to measure reductions in premature NCD mortality using a life table method as specified by the WHO. Multivariate Poisson regression models were used to assess the contributions of individual background factors to decreases in premature NCD mortality. Results: A total of 292,320 deaths occurred in the 30 to 69 year age group during the period 1991 to 2006, against 70,768,848 person-years registered. The crude all-cause mortality rate declined from 5.03 to 3.72 per 1,000 person-years, a 26% reduction. Within this, the unconditional probability of dying between the ages of 30 and 70 from NCD causes as defined by the WHO fell by 30.0%. Age was consistently the strongest determinant of NCD mortality. Background determinants of NCD mortality changed significantly over the four time periods 1991-1994, 1995-1998, 1999-2002, and 2003-2006. Conclusions: Sweden, now at a late stage of epidemiological transition, has already exceeded the 25% premature NCD mortality reduction target during an earlier 15-year period. This should be encouraging news for countries currently implementing premature NCD mortality reduction programmes. Our findings suggest, however, that it may be difficult for Sweden and other late-transition countries to reach the current 25 x 25 target, particularly where substantial premature mortality reductions have already been achieved